most citedSustaining Moore's Law Through Inexactness

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.DS2020

A polynomial time parallel algorithm for graph isomorphism using a quasipolynomial number of processors

Duc Hung Pham, Krishna V. Palem, M. V. Panduranga Rao

The Graph Isomorphism (GI) problem is a theoretically interesting problem because it has not been proven to be in P nor to be NP-complete. Babai made a breakthrough in 2015 when an…

eess.SP2020

The Assurance Monitor Pattern

Adam Duracz, K. Mani Chandy, Mohamed Abdelrahman +5

Some applications require an assurance that certain criteria are violated with only low probability. An alert is generated when the current course of action is likely to violate as…

cs.PL2019

Language Support for Adaptation: Intent-Driven Programming in FAST

Yao-Hsiang Yang, Adam Duracz, Ferenc A. Bartha +7

Historically, programming language semantics has focused on assigning a precise mathematical meaning to programs. That meaning is a function from the program's input domain to its…

cs.LG2019

Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM

Ashesh Chattopadhyay, Pedram Hassanzadeh, Devika Subramanian

In this paper, the performance of three deep learning methods for predicting short-term evolution and for reproducing the long-term statistics of a multi-scale spatio-temporal Lore…

cs.CC20172 cited

Sustaining Moore's Law Through Inexactness

John Augustine, Krishna Palem, Parishkrati

Inexact computing aims to compute good solutions that require considerably less resource -- typically energy -- compared to computing exact solutions. While inexactness is motivate…